• Title/Summary/Keyword: Northeast Asian summer precipitation

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Diagnosis of Northeast Asian Summer Precipitation using the Western North Pacific Subtropical High Index (북서태평양 아열대고기압 지수를 이용한 북동아시아 여름철 강수의 진단)

  • Kwon, MinHo
    • Journal of the Korean earth science society
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    • v.34 no.1
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    • pp.102-106
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    • 2013
  • The intensity of the East Asian summer monsoon has a negative correlation with that of the western North Pacific summer monsoon. Based on the relationship, we suggest the potential predictability of Northeast Asian summer precipitation by using the relationship. The western North Pacific subtropical high (WNPSH) properly represents the intensity of the western North Pacific summer monsoon. It also dominates climate anomalies in the western North Pacific-East Asian region in summertime. The estimates of the Northeast Asian summer rainfall anomalies using WNPSH variability have a greater benefit than those using the western North Pacific monsoon index.

A Prediction of Northeast Asian Summer Precipitation Using the NCEP Climate Forecast System and Canonical Correlation Analysis (NCEP 계절예측시스템과 정준상관분석을 이용한 북동아시아 여름철 강수의 예측)

  • Kwon, MinHo;Lee, Kang-Jin
    • Journal of the Korean earth science society
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    • v.35 no.1
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    • pp.88-94
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    • 2014
  • The seasonal predictability of the intensity of the Northeast Asian summer monsoon is low while that of the western North subtropical high variability is, when state-of-the-art general circulation models are used, relatively high. The western North Pacific subtropical high dominates the climate anomalies in the western North Pacific-East Asian region. This study discusses the predictability of the western North Pacific subtropical High variability in the National Centers for Environmental Prediction Climate Forecast System (NCEP CFS). The interannual variability of the Northeast Asian summer monsoon is highly correlated with one of the western North Pacific subtropical Highs. Based on this relationship, we suggest a seasonal prediction model using NCEP CFS and canonical correlation analysis for Northeast Asian summer precipitation anomalies and assess the predictability of the prediction model. This methodology provides significant skill in the seasonal prediction of the Northeast Asian summer rainfall anomalies.

Analysis of Atmosphere-Ocean Interactions over South China Sea and its Relationship with Northeast Asian Precipitation Variability during Summer (남중국해의 여름철 대기-해양 상호작용과 동아시아 강수량의 상관성 분석)

  • Jang, Hye-Yeong;Yeh, Sang-Wook
    • Atmosphere
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    • v.23 no.3
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    • pp.283-291
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    • 2013
  • This study investigates the changes in the atmosphere-ocean interactions over the South China Sea (SCS) by analyzing their variables in the period of 1979~2011 during the boreal summer (June-July-August). It is found that a simultaneous correlation coefficient between sea surface temperature (SST) and precipitation over SCS during summer is significantly changed before and after the late-1990s. That is, the variation of precipitation over SCS is negatively (positively) correlated with the SST variations before (after) the late-1990s. Our further correlation analysis indicates that the atmospheric forcing of the SST is dominant before the late-1990s accompanying with wind-evaporation feedback and cloud-radiation feedback. After the late-1990s, in contrast, the SST forcing of the atmosphere through the latent heat flux from the ocean to the atmosphere is dominant. It is found that the change in the relationship of atmosphere-ocean interactions over SCS are associated with the changes in the relationship with Northeast Asian summer precipitation. In particular, a simultaneous correlation coefficient between the precipitation over SCS and Northeast Asia becomes stronger during after the late-1990s than before the late-1990s. We argue that the increase of the SST forcing of the atmosphere over SCS may lead a direct relationship of precipitation variations between SCS and Northeast Asia after the late-1990s.

A Prediction of Northeast Asian Summer Precipitation Using Teleconnection (원격상관을 이용한 북동아시아 여름철 강수량 예측)

  • Lee, Kang-Jin;Kwon, MinHo
    • Atmosphere
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    • v.25 no.1
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    • pp.179-183
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    • 2015
  • Even though state-of-the-art general circulation models is improved step by step, the seasonal predictability of the East Asian summer monsoon still remains poor. In contrast, the seasonal predictability of western North Pacific and Indian monsoon region using dynamic models is relatively high. This study builds canonical correlation analysis model for seasonal prediction using wind fields over western North Pacific and Indian Ocean from the Global Seasonal Forecasting System version 5 (GloSea5), and then assesses the predictability of so-called hybrid model. In addition, we suggest improvement method for forecast skill by introducing the lagged ensemble technique.

Performance of NCAR Regional Climate Model in the Simulation of Indian Summer Monsoon (NCAR 지역기후모형의 인도 여름 몬순의 모사 성능)

  • Singh, Gyan Prakash;Oh, Jai-Ho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.12 no.3
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    • pp.183-196
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    • 2010
  • Increasing human activity due to rapid economic growth and land use change alters the patterns of the Asian monsoon, which is key to crop yields in Asia. In this study, we tested the performance of regional climate model (RegCM3) by simulating important components of Indian summer monsoon, including land-ocean contrast, low level jet (LLJ), Tibetan high and upper level Easterly Jet. Three contrasting rain years (1994: excess year, 2001: normal year, 2002: deficient year) were selected and RegCM3 was integrated at 60 km horizontal resolution from April 1 to October 1 each year. The simulated fields of circulations and precipitation were validated against the observation from the NCEP/NCAR reanalysis products and Global Precipitation Climatology Centre (GPCC), respectively. The important results of RegCM3 simulations are (a) LLJ was slightly stronger and split into two branches during excess rain year over the Arabian Sea while there was no splitting during normal and deficient rain years, (b) huge anticyclone with single cell was noted during excess rain year while weak and broken into two cells in deficient rain year, (c) the simulated spatial distribution of precipitation was comparable to the corresponding observed precipitation of GPCC over large parts of India, and (d) the sensitivity experiment using NIMBUS-7 SMMR snow data indicated that precipitation was reduced mainly over the northeast and south Peninsular India with the introduction of 0.1 m of snow over the Tibetan region in April.

A Correction of East Asian Summer Precipitation Simulated by PNU/CME CGCM Using Multiple Linear Regression (다중 선형 회귀를 이용한 PNU/CME CGCM의 동아시아 여름철 강수예측 보정 연구)

  • Hwang, Yoon-Jeong;Ahn, Joong-Bae
    • Journal of the Korean earth science society
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    • v.28 no.2
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    • pp.214-226
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    • 2007
  • Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.